scholarly journals How would information disclosure influence organizations’ outbound spam volume? Evidence from a field experiment

2016 ◽  
Vol 2 (1) ◽  
pp. 99-118 ◽  
Author(s):  
Shu He ◽  
Gene Moo Lee ◽  
Sukjin Han ◽  
Andrew B. Whinston
2021 ◽  
pp. 135481662110346
Author(s):  
Simona Cicognani ◽  
Paolo Figini ◽  
Marco Magnani

We investigate the empirical phenomenon of rating bubbles, that is, the presence of a disproportionate number of extremely positive ratings in user-generated content websites. We test whether customers are influenced by prior ratings when evaluating their stay at a hotel through a field experiment that exogenously manipulates information disclosure. Results show the presence of (asymmetric) social influence bias (SIB): access to information on prior ratings that are above the average positively influences the consumers’ rating of the hotel. In contrast, information on ratings that are below the average does not affect reviewers. Furthermore, customers who have never been to the hotel before the intervention are more susceptible to prior ratings than customers who have repeatedly been to the hotel before. Finally, customers who are not used to writing online reviews are more prone to SIB than customers who frequently write online reviews. Our findings suggest that online rating systems should be adjusted to mitigate this bias, especially as these platforms become more relevant and widespread in the hospitality sector.


2015 ◽  
Vol 105 (2) ◽  
pp. 886-905 ◽  
Author(s):  
Steven Tadelis ◽  
Florian Zettelmeyer

Market outcomes depend on the quality of information available to its participants. We measure the effect of information disclosure on market outcomes using a large-scale field experiment that randomly discloses quality information in wholesale automobile auctions. We argue that buyers in this market are horizontally differentiated across cars that are vertically ranked by quality. This implies that information disclosure helps match heterogeneous buyers to cars of varying quality, causing both good and bad news to increase competition and revenues. The data confirm these hypotheses. These findings have implications for the design of other markets, including e-commerce, procurement auctions, and labor markets. (JEL C93, D44, D82, L15)


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